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Software Engineer Fraud Detection Jobs (NOW HIRING)

ID.me

Senior Fraud Investigations Analyst

Mclean, VA · On-site

... engineering, data, and product teams to enhance fraud detection capabilities and signal quality • Act as an escalation point for high-severity or ambiguous fraud cases • Develop and refine ...

OpenAI

Software Engineer, Scaled Abuse

San Francisco, CA · On-site

The role involves designing and building systems for fraud detection and remediation, collaborating ... Required : • Have at least 5 years of software engineering experience in backend and data systems ...

Rain

Machine Learning Engineer - Fraud Risk

New York, NY · On-site

$50K/yr

Architect and build scalable ML systems for fraud detection, anomaly detection, and behavioral analysis * Develop and maintain end-to-end ML pipelines: data ingestion, feature engineering, model ...

Gianteagle

Knowledge of fraud detection technologies, case management systems, or investigative tools ... Monitor and analyze transactions using analytical tools and software to identify suspicious ...

DataVisor

Software Engineer

Mountain View, CA · On-site

Our award-winning software platform is powered by a team of world-class experts in big data ... As complex fraud attacks become more prevalent, it is more important than ever to detect fraudsters ...

DataVisor

Software Engineer

Mountain View, CA · On-site

Our award-winning software platform is powered by a team of world-class experts in big data ... As complex fraud attacks become more prevalent, it is more important than ever to detect fraudsters ...

DataVisor

Software Engineer

Mountain View, CA · On-site

Our award-winning software platform is powered by a team of world-class experts in big data ... As complex fraud attacks become more prevalent, it is more important than ever to detect fraudsters ...

Giant Eagle

Fraud Analyst,

Cranberry, PA · On-site

Knowledge of fraud detection technologies, case management systems, or investigative tools ... Monitor and analyze transactions using analytical tools and software to identify suspicious ...

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All JobsSoftware Engineer Fraud Detection Jobs

Software Engineer Fraud Detection information

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$24K

$104.9K

$189K

How much do software engineer fraud detection jobs pay per year?

As of Aug 8, 2026, the average yearly pay for software engineer fraud detection in the United States is $104,863.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $120,000.00 per year, depending on experience, location, and employer.

What does a software engineer fraud detection do?

A Software Engineer in Fraud Detection designs and develops systems to identify and prevent fraudulent activities within digital platforms, such as banking or e-commerce environments. They build algorithms to analyze user behavior, detect anomalies, and flag suspicious transactions in real time. Their work often involves machine learning, big data analysis, and close collaboration with data scientists and security teams to continuously improve fraud detection accuracy. These engineers play a key role in protecting businesses and customers from financial loss and cybercrime.

What is the difference between Software Engineer Fraud Detection vs Data Scientist Fraud Detection?

AspectSoftware Engineer Fraud DetectionData Scientist Fraud Detection
Required CredentialsBachelor's in CS or related field, programming skillsBachelor's or higher in CS, Statistics, or Data Science
Work EnvironmentDevelops fraud detection systems, writes code, implements algorithmsAnalyzes data, builds models, interprets results
Employer & Industry UsageFinancial institutions, fintech, e-commerceFinancial services, tech companies, insurance
Common Search & ComparisonFocuses on software development for fraud detectionFocuses on data analysis and modeling for fraud detection

While both roles work in fraud detection, Software Engineer Fraud Detection primarily develops and maintains detection systems through coding, whereas Data Scientist Fraud Detection analyzes data and builds models to identify fraudulent activity. Both roles often collaborate but differ in their core focus and skill sets.

What are the key skills and qualifications needed to thrive as a software engineer fraud detection, and why are they important?

To thrive as a Software Engineer in Fraud Detection, strong programming skills (such as Python, Java, or Scala), a solid understanding of algorithms, data structures, and experience with machine learning or statistical analysis are generally required, often supported by a degree in computer science or a related field. Familiarity with big data platforms (like Hadoop or Spark), real-time analytics systems, and fraud detection tools or frameworks is typically expected. Analytical thinking, problem-solving abilities, and effective communication are key soft skills that differentiate top performers in this field. These skills are crucial for developing robust systems that can quickly identify and prevent fraudulent activities, protecting both users and organizations.

How does a software engineer fraud detection typically collaborate with data scientists and analysts to identify fraudulent activity?

Software Engineers in Fraud Detection work closely with data scientists and analysts to build, refine, and deploy systems that detect and prevent fraud. While data scientists may develop models and identify patterns from large datasets, engineers are responsible for integrating these models into scalable, real-time systems within the company's technology stack. Regular communication and joint problem-solving are essential, as engineers must understand the logic behind models and analysts' findings to ensure accurate implementation and continuous improvement. This collaborative environment helps create robust fraud detection mechanisms that adapt to evolving threats.
More about Software Engineer Fraud Detection jobs
What cities are hiring for Software Engineer Fraud Detection jobs? Cities with the most Software Engineer Fraud Detection job openings:
What states have the most Software Engineer Fraud Detection jobs? States with the most job openings for Software Engineer Fraud Detection jobs include:
What job categories do people searching Software Engineer Fraud Detection jobs look for? The top searched job categories for Software Engineer Fraud Detection jobs are:
Software Engineer Fraud Detection jobs near you
Infographic showing various Software Engineer Fraud Detection job openings in the United States as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $104,863 per year, or $50.4 per hour.

Software Engineer III - Senior Engineer

AiPrise

San Jose, CA • On-site

$185K - $230K/yr

Full-time

Re-posted 13 days ago

Job description

About AiPrise
AiPrise is a YC-backed, Series A company building the global compliance infrastructure for financial services. We help banks, fintechs, cross-border payment providers, stablecoin and crypto companies, and marketplaces gain a 360° view of every business they onboard, anywhere in the world.
Through a single integration, we connect 800+ data sources and 80+ verification partners across 200+ countries, powering KYB, KYC, AML, sanctions screening, and ongoing monitoring for companies like Meta, Airwallex, Fireblocks, and Bridge.
Our AI Agents help compliance teams do more with less, resolving more cases, catching more fraud, and scaling operations without scaling headcount.
We're ~60 people, Series A funded, and obsessed with a single problem: making compliance feel simple for the teams who live in it every day.
Borders shouldn't be blockers. Compliance is hard. AiPrise shouldn't be.
The Role
We are seeking a Senior Software Engineer to join our core engineering team and drive the development of mission-critical features that power compliance for the world's leading financial institutions. You will own significant portions of our platform, from architecting scalable backend systems to designing elegant APIs that serve millions of verification requests. This role offers high autonomy, direct impact on product direction, and the opportunity to mentor engineers while working with cutting-edge technologies including AI-powered fraud detection, distributed systems, and real-time data orchestration. If you thrive in fast-paced environments where your code directly influences how companies fight fraud and ensure compliance globally, this is the role for you.
What You'll Do
Technical Ownership & Delivery
  • Design, build, and maintain core platform features including data orchestration, verification workflows, and API infrastructure that serves customers across 100+ countries

  • Own end-to-end delivery of complex features from technical design through deployment, monitoring, and iteration based on customer feedback

  • Write clean, well-tested, and performant code with strong attention to system reliability, scalability, and security - critical in our regulated compliance environment

  • Drive architectural decisions for your domain, balancing technical excellence with pragmatic delivery to support rapid product iteration

  • Collaborate closely with product managers and designers to translate customer needs and compliance requirements into technical solutions

Leadership & Collaboration
  • Mentor and pair with engineers across the team, conducting thoughtful code reviews and sharing knowledge to elevate engineering standards

  • Participate in on-call rotation to ensure platform reliability and lead incident response when systems need attention

  • Contribute to engineering culture through process improvements, technical documentation, and advocating for engineering best practices

  • Partner with cross-functional teams including customer success, sales, and operations to understand customer pain points and deliver solutions that delight users

  • Influence technical roadmap and architecture decisions through RFCs, design reviews, and strategic technical discussions

  • Innovation & Technical Excellence

  • Stay current with emerging technologies and bring innovative approaches to fraud detection, data processing, and compliance automation

  • Contribute to our AI-powered features including document intelligence, website analysis, and anomaly detection systems

  • Identify and drive technical improvements to reduce technical debt, improve system performance, and enhance developer productivity

Requirements
  • Bachelor's degree in Computer Science, Engineering, a related technical field, or equivalent practical experience
  • 5+ years of professional software engineering experience building production systems
  • Strong programming skills in modern languages (we primarily use Python, Go, and TypeScript/Node.js)
  • Deep understanding of backend systems, distributed architectures, API design, and database optimization (SQL and NoSQL)
  • Experience building scalable systems that handle high throughput and maintain reliability under load
  • Track record of owning complex technical projects from conception to successful delivery
  • Strong communication skills with ability to explain technical concepts to both technical and non-technical stakeholders
  • Experience mentoring junior engineers and contributing to engineering culture

Bonus Points
  • Experience in fintech, compliance, identity verification, or fraud detection domains

  • Familiarity with AI/ML systems, document processing, or computer vision applications

  • Experience with cloud platforms (AWS, GCP, or Azure) and modern infrastructure tools (Docker, Kubernetes, Terraform)

  • Contributions to open source projects or technical communities

  • Experience working in high-growth startup environments with rapidly evolving requirements

  • Knowledge of global compliance regulations (KYC, KYB, AML, GDPR)

Why AiPrise
  • Direct Impact: Your code will process millions of verifications and help prevent fraud for leading financial institutions globally
  • Technical Challenges: Work on complex problems at the intersection of compliance, AI, fraud detection, and distributed systems
  • Ownership & Autonomy: Lead major technical initiatives with significant influence over architecture and product direction
  • Learning & Growth: Work alongside talented engineers, access to cutting-edge technologies, and clear career progression to Staff Engineer and beyond
  • Global Reach: Build infrastructure used across 100+ countries with diverse technical and regulatory requirements
  • Competitive Compensation: Market-rate salary, meaningful equity, comprehensive benefits, and flexible remote work options

Apply